A non-destructive method for quantification the irradiation doses of irradiated sucrose using Vis/NIR spectroscopy.

This article proposes a new method for fast discrimination of irradiation doses of sucrose based on visible-near infrared (Vis/NIR) spectroscopy technology. 250 sucrose samples were categorized into five groups to be irradiated at 0, 1.5, 3.0, 4.5, 6.0 kGy respectively and prepared for the discrimination analysis. The 50 samples of each group were randomly divided into a calibration set containing 40 samples, and a validation set containing the remaining 10 samples. Principal component clustering analysis (PCCA) was applied for the extraction of principal components (PCs) and for clustering analysis. The first five PCs were regarded as the inputs to develop the back propagation neural network (BPNN) model. The performance of the model was validated by the 50 unknown samples and the BPNN achieved an excellent precision and recognition ration of 100%. The results indicated that Vis/NIR spectroscopy could be utilized as a rapid and non-destructive method for the classification of different irradiation doses of irradiated sucrose.